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Fingerprinting JPEGs With Optimised Huffman Tables

McKeown, Sean; Russell, Gordon; Leimich, Petra

Authors



Abstract

A common task in digital forensics investigations is to identify known contraband images. This is typically achieved by calculating a cryptographic digest, using hashing algorithms such as SHA256, for each image on a given medium, and comparing individual digests with a database of known contraband. However, the large capacities of modern storage media and time pressures placed on forensics examiners necessitates the development of more efficient processing methods. This work describes a technique for fingerprinting JPEGs with optimised Huffman tables which requires only the image header to be present on the media. Such fingerprints are shown to be robust across large datasets, with demonstrably faster processing times.

Citation

McKeown, S., Russell, G., & Leimich, P. (2018). Fingerprinting JPEGs With Optimised Huffman Tables. Journal of Digital Forensics, Security and Law, 13(2), Article 7. https://doi.org/10.15394/jdfsl.2018.1451

Journal Article Type Article
Acceptance Date Oct 12, 2017
Publication Date 2018-10
Deposit Date Oct 18, 2017
Publicly Available Date Oct 18, 2017
Journal The Journal of Digital Forensics, Security and Law
Print ISSN 1558-7215
Electronic ISSN 1558-7223
Publisher Association of Digital Forensics, Security and Law
Peer Reviewed Peer Reviewed
Volume 13
Issue 2
Article Number 7
DOI https://doi.org/10.15394/jdfsl.2018.1451
Keywords digital forensics, image comparison, image processing, known file analysis, partial file analysis
Public URL http://researchrepository.napier.ac.uk/Output/997464
Publisher URL http://commons.erau.edu/jdfsl/

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Publisher Licence URL
http://creativecommons.org/licenses/by-nc/4.0/

Copyright Statement
This Article is brought to you for free and open access by the Journals at
Scholarly Commons. It has been accepted for inclusion in Journal of Digital Forensics, Security and Law by an authorized administrator of Scholarly Commons. For more information, please contact commons@erau.edu







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